Sr Data Scientist, Customer Success

Key Skills

Python Programming, Scala Programming, C++, Java Programming, Machine learning techniques, Data science techniques, SQL, Apache Hadoop, MapReduce, TensorFlow, PyTorch, R Programming

Job Description

You will be a first Data Scientist for the Customer Success team. You will have an opportunity to lay the foundation of the data and analytics powerhouse of the CS team and scale your team over time and use AI&ML capacities to inform business decisions.

On a weekly basis, you will build data pipelines around product telemetry, business systems data, and aggregated tables. This will become a foundation and enable you to expand the responsibilities into analytics and predictions. As part of the broader CS Organization, you will continue to strengthen your technical expertise through mentorship, continuous learning, and internal training programs.

The impact you will have:

• Develop deep understanding of the metrics that drive Customer Success and manage the data layer to provide visibility into this metrics, timely reporting, and self-service tooling for Customer Success teams
• Productionalize and unify existing data pipelines that are used across CS teams.
• Become an expert in product telemetry and business systems data, work with CS teams to understand customer usecases to identify behaviour patterns that drive consumption of Databricks products
• Work with business stakeholders to operationalize insights and help customer-facing teams to be more productive by using your insights.
• Ensure data quality across various systems of record and flag areas of continuous improvement for our data lake
• Address deep-dive questions by the Customer Success leadership team with follow up insights and recommended actions

What we look for:

• Hands-on and superior technical experience with Apache Spark
• Proven experience of design and implementation experience in big data technologies including Hadoop, NoSQL, MPP, OLTP, and OLAP
• 5+ years experience as Data Scientist/ML Engineer: model selection, model lifecycle, hyperparameter tuning, model serving, deep learning, etc.
• 3+ years experience as Software Engineer/Data Engineer: query tuning, performance tuning, troubleshooting, and debugging Spark or other big data solutions.
• Comfortable programming in Python, Scala or Java
• Experience using and designing solutions on cloud infrastructure and services, such as AWS, Azure, or GCP
• Experience with Development Tools for CI/CD, Unit and Integration testing, Automation and Orchestration, REST API, BI tools and SQL Interfaces. E.g. Jenkins
• Proven experience with ML concepts covering Model Tracking, Model Serving and other aspects of productionizing ML pipelines in distributed data processing environments like Apache Spark, using tools like MLflow
• Excellent communication skills and comfortable presenting to strategic stakeholders/leadership
• Experience in customer-facing pre-sales, post-sales, technical architecture guidance, or consulting
• Passionate about learning new technologies and making customers successful